July 2019 Summaries

Apache Kafka and MongoDB are integral components of contemporary data architectures, where Kafka serves as an event streaming platform and MongoDB as a versatile database for large volumes of diverse data. The integration of these systems is facilitated through Kafka Connect, which enables seamless data streaming between external systems and Kafka topics. The MongoDB Connector for Apache Kafka, developed and maintained by MongoDB Inc., allows MongoDB to act as both a source and a sink for Kafka, supporting scenarios such as event-driven architectures and microservices. This connector can be installed via Confluent Hub either automatically or manually, providing flexibility in deployment. The document further illustrates practical use cases of this integration, such as an e-commerce scenario where MongoDB and Kafka are used to manage inventory data and notify systems for reordering products, and another where new user information is propagated across business systems. Additionally, the text touches on MongoDB's leadership transition, with Dev Ittycheria announcing his retirement as CEO by 2025, and Chirantan “CJ” Desai being named as his successor, highlighting Desai's extensive experience and suitability to guide MongoDB through its next phase of growth.

Introducing the MongoDB Enterprise Operator for Kubernetes` is a tool that enables users to deploy and manage MongoDB clusters from within the Kubernetes API. It provides benefits such as deploying, scaling, and automating MongoDB clusters of any type or size, enforcing standardized cluster configurations, and providing centralized logging. The operator works with MongoDB Ops Manager or MongoDB Cloud Manager and can run on various Kubernetes distributions. To get started, users need access to an Ops Manager environment or MongoDB Cloud Manager, a compatible Kubernetes environment, and create a ConfigMap file with Ops Manager configuration information. They also need to create a Secret object for the Public API Key. The operator provides features such as persistent storage, connecting applications, basic troubleshooting, and more. It is designed to support cloud-native apps with Kubernetes and provides granular control over deployments, consistency, and log management.

The MongoDB blog discusses how to create properties in a schema that are dependent on other properties, which allows for more sophisticated validation and data modeling. Property dependencies state that if one property is present, others must also be present, while schema dependencies define changes to the schema based on the presence of another property. The blog provides examples of both types of dependencies and demonstrates how they can be used to enforce complex validation rules in MongoDB. Additionally, it mentions MongoDB Stitch's validate expression feature, which allows for more advanced validation using Stitch functions.

The Compass BSON transpiler plugin allows developers to work in their chosen programming language when using MongoDB Compass, enabling flexibility and ease of use. The plugin leverages the open-source parsing tool ANTLR to minimize complexity and supports multiple input languages (MongoDB Shell, JavaScript, and Python) and output languages (Java, C#, Python, MongoDB Shell, and JavaScript). The transpiler is built as a standalone Node.js module and can be used in any browser-based or Node.js application. It uses a modular design, allowing users to contribute new input and output languages without requiring knowledge of existing languages. The plugin's latest version includes additional features such as support for a wider range of syntax through the use of a symbol table, function calls with arguments, type validation, and informative error messages.